Students learn when to trust the model and when to override it.
Flexee Data Analytics puts student teams in a competitive simulated market. Across six analytics modules, students download data each quarter, analyze it in Excel, Python, R, or SPSS, and commit to decisions the market then judges. Six AI advisors help teams think each decision through, and the final call stays with the team.
Analysis that gets tested by the market.
Students run regressions, build models, and read confidence intervals, then use that analysis to make decisions with consequences. Each quarter, the market shows them whether the analysis helped.
Teams compete in the same market and get full financial statements each quarter. Between quarters they work in the Analytics Workbench, downloading data, running their own analysis in the tools analysts use at work, and committing to decisions the market judges. The GUT-vs-MODEL tracker follows each team across rounds and shows whether their analysis beat their instinct.
At the end of the simulation, students compare the forecast error (mean absolute percentage error, or MAPE) of their model-driven and gut-driven decisions across the whole run. It tells them plainly whether the analysis paid off.
Analysis that changes decisions.
The tools analysts use.
Students download simulation data between quarters and work in Excel, Python, R, or SPSS, the same tools they'll use at work. What they find in their analysis decides what they commit to in the simulation.
The GUT-vs-MODEL tracker.
Before committing, every team records both its gut estimate and its model's output. The tracker follows both across quarters, so students see whether their analysis is beating their instinct and where their models keep missing.
Consequences the model didn't predict.
Even strong analysis gets surprised by competitor moves, market shifts, and events the historical data didn't contain. Students learn what analytics is good for and when to hold a model's predictions loosely, because they've been surprised themselves.
Each module teaches a different analytics skill.
Faculty can turn on all six modules for a full analytics course, or choose the ones that fit the syllabus. Each module comes with its own data and analysis goals, and its results play out in the simulation.
Built for analytics courses.
Multi-quarter competitive simulation.
Teams compete in the same market across multiple quarters, with financial results, competitor moves, and market feedback every round.
Faculty set the schedule.
Faculty set the schedule for their course, including orientation weeks, when each module unlocks, and the dates for each round.
MAPE tells students whether the analytics work paid off.
At the end of the simulation, the MAPE comparison shows how much better or worse students' model-driven decisions did than their gut-driven decisions over the whole run. Faculty use it to lead the debrief on when to trust a model, when to override it, and how far to rely on it.
See if Flexee Data Analytics fits your business analytics course.
Flexee Data Analytics is in use today in business analytics programs, MBA analytics concentrations, and executive education. Talk to Chuck about how the six modules would fit your syllabus.